A NOVEL TECHNIQUE FOR IRIS RECOGNITION SYSTEM

Amir Azizi

(Eqbal Institute of Higher Education, Mashhad, Iran)

(http://research.eqbal.ac.ir)

IJCCI 2009 - International Joint Conference on Computational Intelligence,2009

Abstract:

In this paper we propose a new feature extraction method for iris recognition based on contourlet transform.Contourlet transform captures the intrinsic geometrical structures of iris image. It decomposes the iris image into a set of directional sub-bands with texture details captured in different orientations at various scales so for reducing the feature vector dimensions we use the method for extract only significant bit and information from normalized iris images. In this method we ignore fragile bits. At last, the feature vector is created by using Co-occurrence matrix properties. For analyzing the desired performance of our proposed method, we use the CASIA dataset, which is comprised of 108 classes with 7 images in each class and each class represented a person. And finally we use SVM and KNN classifier for approximating the amount of people identification in our proposed system. Experimental results show that the proposed increase the classification accuracy and also the iris feature vector length is much smaller versus the other methods.

Keywords:

Biometric,Iris Recognition,Contourlet Transform,Co-occurrence matrix.